MLSE equalisation is a well-known technique described, for example, in J. G. Proakis, “Digital Communications”, McGraw Hill, 3/e 1995. The technique is described in detail below but, broadly speaking, an estimate is made of a sequence of symbols representing binary bits by hypothesising received symbol sequences, applying to the hypothesised sequences a channel estimate for a channel over which data has been transmitted, and comparing the result with the received data to see which estimated hypothesised sequence is the closest match. Typically the best match is found by determining the minimum mean-square error (MMSE), although other metrics may also be employed, and generally the procedure is implemented using a variant of the Viterbi algorithm.
The channel estimate comprises a set of numbers which models the transmission channel, for example comprising a complex number representing a magnitude and phase of the channel response at a particular delay. The channel response may be determined at delays of integer multiples of the symbol period, in effect defining a set of multipath components. Generally the channel response decreases at longer delays and it becomes zero after the longest multipath delay. In a digital system there may be more than one sample per symbol and, in this case, the channel response may be defined at a finer time resolution. All this is well known to the skilled person.
As the symbol period becomes significant compared to the time dispersion of the wireless channel Inter-Symbol Interference (ISI) degrades the performance of a receiver for data transmitted through the channel. The Maximum Likelihood metric provides optimal reception of data with ISI but is relatively complex to implement. However where the time dispersion is relatively small, so that there are relatively few multipath components to consider at symbol-spaced delays, the quantities of data to be processed are reduced. This is the case, for example, with short range radio links such as high rate Bluetooth (Trade Mark) links. Aspects of the invention will therefore be described with reference to the High Rate Bluetooth link specification, although it should be understood that applications of the invention are not limited to this type of link.
The Bluetooth group of standards is concerned with short range (up to around 10 meters) rf transmission as a replacement for cables. The basic standard provides a frequency hopping spread spectrum (FHSS) link operating at 0.7 Mbps (V 1.1) or 2.1 Mbps (V 1.2). High rate Bluetooth has a maximum user bit rate of 11.4 Mbps and is associated with the IEEE 802.15 group of standards, in particular IEEE 802.15.3.
The performance of a digital rf link can be improved by using coherent or pseudo-coherent detection and by employing multiple antennas and/or equalisation. Maximum likelihood sequence estimation is one form of non-linear equalisation which, conventionally, uses a predefined training sequence of bits, known at the receiver, to derive an estimate of the channel response. Such channel estimation is conventionally performed every time a new packet is received. MLSE-type equalisers provide good performance as long as an accurate estimate of the channel can be derived at the receiver. One of the aims of the invention is to provide improved methods and apparatus for channel estimation during the equalisation process.
Optimum channel estimation generally requires long training sequences and waste transmission bandwidth. Conventionally, once the transmission channel has been estimated the system does not track variations in the channel while receiving a packet so that for a subsequent packet an equally long training sequence is required, whether or not the channel estimate has in practice changed.
U.S. Pat. No. 6,275,525 describes an MLSE technique in which an initial channel estimation provides the information needed to perform the MLSE, and in which the channel estimate is then updated based upon tentative, adaptive decisions made on the received data. This improves upon the basic MLSE technique, but introduces a delay and leaves room for further improvement in the channel estimation procedure.
U.S. Pat. No. 6,373,888 describes a technique in which a plurality of channel estimates is generated from a training sequence by using a plurality of (channel) filter models, selecting models with different numbers and positions of taps. The model with the best fit to the training data, that is the least residual error, is then used for decoding according to the Viterbi algorithm.
WO 00/44141 describes an MLSE technique in which look-up tables are constructed by pre-computing complex hypothesised received symbol values (or sample values) by operating on hypothesised transmitted symbols with channel tap estimates. This is specifically described at page 8 line 11 to page 9 line 23 (with reference to FIG. 7) and page 12 line 3 to page 13 line 2 (with reference to FIGS. 8-11) of WO 00/44141, which specific extracts from '141 are hereby incorporated by reference.
The present invention addresses, among other things, the problem of providing more frequent and accurate channel estimations and, more particularly, the problem of tracking the channel variation.